Tootfinder

CyberArmor has a post up detailing abuse of the Vercel app development platform. Vercel is a legit tool that allows for the rapid creation of web applications. They have a free tier and unfortunately it gets abused. The free tier apps use the domain pattern *.vercel.app. I recommend blocking this domain and only allowing access to vetted sites using this domain name. Note that commercial sites using the Vercel platform will have their own domain names so your potential for collateral damage …

Massless monopole-string-domain wall fermions and polyhedral vacuum fermions
Minoru Eto, Yuito Suzuki
https://arxiv.org/abs/2506.16765 https://

Massless monopole-string-domain wall fermions and polyhedral vacuum fermions
Fermion zero modes of Bogomol'nyi-Prasad-Sommerfield monopole-string-domain wall composites in three spatial dimensions are studied. We analytically solve the Dirac equation and prove the existence of one fermion zero mode. Depending on mass parameters of bosons/fermions in the model, the zero modes are localized either on the monopoles, strings or domain walls, which we call monopole-string-domain wall fermions. We also show that in special cases, the zero modes can be confined within a finite…

General-domain FC-based shock-dynamics solver I: Basic elements
Oscar P. Bruno, Daniel V. Leibovici
https://arxiv.org/abs/2506.16076 https://

General-domain FC-based shock-dynamics solver I: Basic elements
This contribution, Part I in a two-part article series, presents a general-domain version of the FC-SDNN (Fourier Continuation Shock-detecting Neural Network) spectral scheme for the numerical solution of nonlinear conservation laws, which is applicable under arbitrary boundary conditions and in general domains. Like the previous simple-domain contribution (Journal of Computational Physics X 15, (2022)), the present approach relies on the use of the Fourier Continuation method for accurate spec…

D2Diff : A Dual Domain Diffusion Model for Accurate Multi-Contrast MRI Synthesis
Sanuwani Dayarathna, Himashi Peiris, Kh Tohidul Islam, Tien-Tsin Wong, Zhaolin Chen
https://arxiv.org/abs/2506.15750

D2Diff : A Dual Domain Diffusion Model for Accurate Multi-Contrast MRI Synthesis
Multi contrast MRI synthesis is inherently challenging due to the complex and nonlinear relationships among different contrasts. Each MRI contrast highlights unique tissue properties, but their complementary information is difficult to exploit due to variations in intensity distributions and contrast specific textures. Existing methods for multi contrast MRI synthesis primarily utilize spatial domain features, which capture localized anatomical structures but struggle to model global intensity …

TIL in 2017 the UK Payments Administration renamed themselves "Pay.UK" but have not obtained the domain registration for pay.uk
(This isn't a "forgot to register" situation - open .uk registration between 2014 and 2019 was reserved for equivalent co.uk holders. The domain was registered by the holder two weeks before it would have been available.)

Multi-Domain Optimization Framework for ISAC: From Electromagnetic Shaping to Network Cooperation
Rang Liu, Ming Li, Mehdi Zafari, Bjorn Ottersten, A. Lee Swindlehurst
https://arxiv.org/abs/2506.16011

Multi-Domain Optimization Framework for ISAC: From Electromagnetic Shaping to Network Cooperation
Integrated sensing and communication (ISAC) has emerged as a key feature for sixth-generation (6G) networks, providing an opportunity to meet the dual demands of communication and sensing. Existing ISAC research primarily focuses on baseband optimization at individual access points, with limited attention to the roles of electromagnetic (EM) shaping and network-wide coordination. The intricate interdependencies between these domains remain insufficiently explored, leaving their full potential f…

Generalized Eshelby's inclusion and inhomogeneity problems for transient heat transfer
Chunlin Wu, Zhenhua Wei, Huiming Yin
https://arxiv.org/abs/2506.16498

Generalized Eshelby's inclusion and inhomogeneity problems for transient heat transfer
Eshelby's problems have been generalized to arbitrary shape of polygonal, polyhedral, and ellipsoidal inclusions embedded in an infinite isotropic domain under transient heat transfer, and Eshelby's tensors have been analytically derived to evaluate disturbed thermal fields caused by inclusions with a polynomial-form eigen-fields. Transformed coordinates are applied to arbitrarily shaped inclusions for domain integrals of transient fundamental solutions. This formulation is for general transien…

I use a Cloudflare tunnel which, among other things, requires a 2FA code. A code number that I was not receiving... Why? Because I'm so stupid that I was using the old Proton Mail domain (protonmail.com) instead of the new one (proton.me), not remembering that my Cloudflare account was associated with the latter.
I am the weakest link in my own chain.

Active, reactive and instantaneous optical forces on small particles in the time domain: Ultrafast attosecond subcycle pulses
Xiaohao Xu, Francisco J. Valdivia Valero, Manuel Nieto-Vesperinas
https://arxiv.org/abs/2506.15917

Active, reactive and instantaneous optical forces on small particles in the time domain: Ultrafast attosecond subcycle pulses
Recently discovered reactive optical forces have nule time-average of their instantaneous values on monochromatic illumination, so that their detection suggests the use of ultrafast optics, specially in the femto and attosecond domains. By using illumination with subcycle attosecond evanescent pulses, we report a theoretical study of the time variations of reactive forces versus those of active and instantaneous ones on small resonant particles that we consider dipolar; and show their correspon…

Domain Generalization for Person Re-identification: A Survey Towards Domain-Agnostic Person Matching
Hyeonseo Lee, Juhyun Park, Jihyong Oh, Chanho Eom
https://arxiv.org/abs/2506.12413

Domain Generalization for Person Re-identification: A Survey Towards Domain-Agnostic Person Matching
Person Re-identification (ReID) aims to retrieve images of the same individual captured across non-overlapping camera views, making it a critical component of intelligent surveillance systems. Traditional ReID methods assume that the training and test domains share similar characteristics and primarily focus on learning discriminative features within a given domain. However, they often fail to generalize to unseen domains due to domain shifts caused by variations in viewpoint, background, and l…

Fine-Tuning Lowers Safety and Disrupts Evaluation Consistency
Kathleen C. Fraser, Hillary Dawkins, Isar Nejadgholi, Svetlana Kiritchenko
https://arxiv.org/abs/2506.17209

Fine-Tuning Lowers Safety and Disrupts Evaluation Consistency
Fine-tuning a general-purpose large language model (LLM) for a specific domain or task has become a routine procedure for ordinary users. However, fine-tuning is known to remove the safety alignment features of the model, even when the fine-tuning data does not contain any harmful content. We consider this to be a critical failure mode of LLMs due to the widespread uptake of fine-tuning, combined with the benign nature of the "attack". Most well-intentioned developers are likely unaware that th…

interactome_pdz: PDZ-domain interactome (2005)
A network of PDZ-domain-mediated protein–protein binding interactions, extracted from the PDZBase database. Nodes represent proteins and an edge represents a binding interaction between two proteins.
This network has 212 nodes and 244 edges.
Tags: Biological, Protein interactions, Unweighted

Comparison of substructured non-overlapping domain decomposition and overlapping additive Schwarz methods for large-scale Helmholtz problems with multiple sources
Boris Martin, Pierre Jolivet, Christophe Geuzaine
https://arxiv.org/abs/2506.16875

Comparison of substructured non-overlapping domain decomposition and overlapping additive Schwarz methods for large-scale Helmholtz problems with multiple sources
Solving large-scale Helmholtz problems discretized with high-order finite elements is notoriously difficult, especially in 3D where direct factorization of the system matrix is very expensive and memory demanding, and robust convergence of iterative methods is difficult to obtain. Domain decomposition methods (DDM) constitute one of the most promising strategy so far, by combining direct and iterative approaches: using direct solvers on overlapping or non-overlapping subdomains, as a preconditi…

#Wordle 1,433 5/6*
⬜⬜🟨⬜⬜ <1% of 212,891 (265)
⬜⬜⬜🟩🟨 0 of 58 (10)
⬜⬜🟩🟩⬜ 0 of 0 (2)
⬜⬜🟩🟩⬜ 0 of 0 (1)
🟩🟩🟩🟩🟩
WordleBot
Skill 97/99
Luck 38/99
Wasn't sure that last guess was really a good 5th guess, but decided it would provide useful info even if wrong.
Look at that I actually narrowed it to 2 and used my friend @… 's patented method of trying all the wrong answers first to get it! 😁 She said she's going to put it in the public domain, so anyone else is also free to use it!

More sites like this: https://infosec.exchange/@gabe_sky/114558396307371647
I have:
https://countdown.codevoid.net

A System Level Compiler for Massively-Parallel, Spatial, Dataflow Architectures
Dirk Van Essendelft, Patrick Wingo, Terry Jordan, Ryan Smith, Wissam Saidi
https://arxiv.org/abs/2506.15875

A System Level Compiler for Massively-Parallel, Spatial, Dataflow Architectures
We have developed a novel compiler called the Multiple-Architecture Compiler for Advanced Computing Hardware (MACH) designed specifically for massively-parallel, spatial, dataflow architectures like the Wafer Scale Engine. Additionally, MACH can execute code on traditional unified-memory devices. MACH addresses the complexities in compiling for spatial architectures through a conceptual Virtual Machine, a flexible domain-specific language, and a compiler that can lower high-level languages to m…

A Prior-Guided Joint Diffusion Model in Projection Domain for PET Tracer Conversion
Fang Chen, Weifeng Zhang, Xingyu Ai, BingXuan Li, An Li, Qiegen Liu
https://arxiv.org/abs/2506.16733

A Prior-Guided Joint Diffusion Model in Projection Domain for PET Tracer Conversion
Positron emission tomography (PET) is widely used to assess metabolic activity, but its application is limited by the availability of radiotracers. 18F-labeled fluorodeoxyglucose (18F-FDG) is the most commonly used tracer but shows limited effectiveness for certain tumors. In contrast, 6-18F-fluoro-3,4-dihydroxy-L-phenylalanine (18F-DOPA) offers higher specificity for neuroendocrine tumors and neurological disorders. However, its complex synthesis and limitations in transportation and clinical …

Doing a more extensive SI/PI workup on the switch line card in preparation for a) a blog update on the switch project and b) getting all my I's dotted and T's crossed before spending a lot of money stuffing three more boards and ordering the logic board.
Here's the 2.5V rail, putting out a bit over 2A at 2.5V. Ripple is dominated by ~300 kHz switching noise plus some harmonics of the 125 MHz PHY symbol rate (which makes sense this rail is driving the PHY PAM5 transceivers a…

Ahlfors-regularity for minimizers of a multiphase optimal design problem
Luca Esposito, Lorenzo Lamberti, Giovanni Pisante
https://arxiv.org/abs/2506.15861

Ahlfors-regularity for minimizers of a multiphase optimal design problem
We establish an Alhfors-regularity result for minimizers of a multiphase optimal design problem. It is a variant of the classical variational problem which involves a finite number of chambers $\mathcal{E}(i)$ of prescribed volume that partition a given domain $Ω\subset\mathbb{R}^n$. The cost functional associated with a configuration $\left(\{\mathcal{E}(i)\}_i,u\right)$ is made up of the perimeter of the partition interfaces and a Dirichlet energy term, which is discontinuous across the inte…

High resolution radio observations of the Chamaeleon star-forming region
Ernesto Garc\'ia Valencia, Laurent Loinard, Arnaud Belloche, Gisela N. Ortiz Le\'on, Sergio A. Dzib, Cherie K. Day, Roopesh Ojha
https://arxiv.org/abs/2506.15927

High resolution radio observations of the Chamaeleon star-forming region
We report on large-scale radio observations of the Chamaeleon star-forming region obtained with the Australia Telescope Compact Array (ATCA) that led to the definite detection of five young stars and the tentative detection of five more. As in other regions surveyed in the radio domain, the majority of detected sources are fairly evolved low-mass T Tauri stars, but we also detect one protostellar object (Ced 110 IRS4) and one Herbig Ae/Be star. With the exception of the protostellar source, the…

Pre-training Time Series Models with Stock Data Customization
Mengyu Wang, Tiejun Ma, Shay B. Cohen
https://arxiv.org/abs/2506.16746 https://

Pre-training Time Series Models with Stock Data Customization
Stock selection, which aims to predict stock prices and identify the most profitable ones, is a crucial task in finance. While existing methods primarily focus on developing model structures and building graphs for improved selection, pre-training strategies remain underexplored in this domain. Current stock series pre-training follows methods from other areas without adapting to the unique characteristics of financial data, particularly overlooking stock-specific contextual information and the…

Bidder Feedback in First-Price Auctions for Video Advertising
S\'ebastien Lahaie, Benjamin Schaeffer, Yuanjun Zhou
https://arxiv.org/abs/2506.17058 htt…

Bidder Feedback in First-Price Auctions for Video Advertising
In first-price auctions for display advertising, exchanges typically communicate the "minimum-bid-to-win" to bidders after the auction as feedback for their bidding algorithms. For a winner, this is the second-highest bid, while for losing bidders it is the highest bid. In this paper we investigate the generalization of this concept to general combinatorial auctions, motivated by the domain of video advertising. In a video pod auction, ad slots during an advertising break in a video stream are …

AeroGPT: Leveraging Large-Scale Audio Model for Aero-Engine Bearing Fault Diagnosis
Jiale Liu, Dandan Peng, Huan Wang, Chenyu Liu, Yan-Fu Li, Min Xie
https://arxiv.org/abs/2506.16225

AeroGPT: Leveraging Large-Scale Audio Model for Aero-Engine Bearing Fault Diagnosis
Aerospace engines, as critical components in aviation and aerospace industries, require continuous and accurate fault diagnosis to ensure operational safety and prevent catastrophic failures. While deep learning techniques have been extensively studied in this context, they output logits or confidence scores, necessitating post-processing to derive actionable insights. Furthermore, the potential of large-scale audio models in this domain remains largely untapped. To address these limitations, t…

So, it's not possible to turn off the AI Overview in Google on a Workspace for Education account at the admin level, so the only way to prevent students from access to AI products is to block Google entirely.
But Google says AI Overviews are part of Google Search...
Looking for a search to leave unblocked for students.
(Not DuckDuckGo, they have AI chat right on their home domain now.)
#education

Crowned Lie groups and nets of real subspaces
Daniel Beltita, Karl-Hermann Neeb
https://arxiv.org/abs/2506.16422 https://arxiv.org/pd…

Crowned Lie groups and nets of real subspaces
We introduce the notion of a complex crown domain for a connected Lie group $G$, and we use analytic extensions of orbit maps of antiunitary representations to these domains to construct nets of real subspaces on $G$ that are isotone, covariant and satisfy the Reeh--Schlieder and Bisognano--Wichmann conditions from Algebraic Quantum Field Theory. This provides a unifying perspective on various constructions of such nets.The representation theoretic properties of different crowns are discussed i…

This https://arxiv.org/abs/2504.02966 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

On deformation of perfectoid purity in Gorenstein domains
If $(R,\mathfrak{m})$ is a complete local ring of mixed characteristic $(0,p)$ and $R/pR$ is an $F$-pure Gorenstein domain, we find a sufficient condition for $R$ to be perfectoid pure. This condition is related to the Cohen-Macaulayness of the absolute integral closures of Gorenstein local domains of mixed characteristic which are not necessarily excellent. Along the way, we show that the problem of lifting $F$-purity of $R/pR$ to perfectoid purity of $R$ is equivalent to a similar deformation…

AI research nonprofit EleutherAI releases the Common Pile v0.1, an 8TB dataset of licensed and open-domain text for AI models that it says is one of the largest (Kyle Wiggers/TechCrunch)
https://techcrunch.com/2025/06/06/eleu

EleutherAI releases massive AI training dataset of licensed and open domain text | TechCrunch
EleutherAI, an AI research organization, has released what it's claiming is one of the largest collections of licensed and open-domain text for training AI models.

"We think of generating source code from a prompt as an AI-powered feature of modern IDEs, but the general problem has a rich history in research efforts and domain-specific programming systems." Join William Benton at this year's Berlin Buzzwords to hear him talk about the history of program synthesis, its relationship to the history of AI, and the lessons we can learn from it today.
Learn more:

Large solutions for subordinate spectral Laplacian
Ivan Bio\v{c}i\'c, Vanja Wagner
https://arxiv.org/abs/2506.16780 https://arxiv…

Large solutions for subordinate spectral Laplacian
We find a large solution to a semilinear Dirichlet problem in a bounded $C^{1,1}$ domain for a non-local operator $ϕ(-Δ\vert_{D})$, an extension of the infinitesimal generator of a subordinate killed Brownian motion. The setting covers and extends the case of the spectral fractional Laplacian. The upper bound for the explosion rate of the large solution is obtained, and is given in terms of the renewal function, distance to the boundary, and the Keller-Osserman-type transformation of the semi…

Enhanced Dermatology Image Quality Assessment via Cross-Domain Training
Ignacio Hern\'andez Montilla, Alfonso Medela, Paola Pasquali, Andy Aguilar, Taig Mac Carthy, Gerardo Fern\'andez, Antonio Martorell, Enrique Onieva
https://arxiv.org/abs/2506.16116

Enhanced Dermatology Image Quality Assessment via Cross-Domain Training
Teledermatology has become a widely accepted communication method in daily clinical practice, enabling remote care while showing strong agreement with in-person visits. Poor image quality remains an unsolved problem in teledermatology and is a major concern to practitioners, as bad-quality images reduce the usefulness of the remote consultation process. However, research on Image Quality Assessment (IQA) in dermatology is sparse, and does not leverage the latest advances in non-dermatology IQA,…

Expert-in-the-Loop Systems with Cross-Domain and In-Domain Few-Shot Learning for Software Vulnerability Detection
David Farr, Kevin Talty, Alexandra Farr, John Stockdale, Iain Cruickshank, Jevin West
https://arxiv.org/abs/2506.10104

Expert-in-the-Loop Systems with Cross-Domain and In-Domain Few-Shot Learning for Software Vulnerability Detection
As cyber threats become more sophisticated, rapid and accurate vulnerability detection is essential for maintaining secure systems. This study explores the use of Large Language Models (LLMs) in software vulnerability assessment by simulating the identification of Python code with known Common Weakness Enumerations (CWEs), comparing zero-shot, few-shot cross-domain, and few-shot in-domain prompting strategies. Our results indicate that while zero-shot prompting performs poorly, few-shot prompti…

Nonlinear random perturbations of Reaction-Diffusion Equations
Sandra Cerrai, Giuseppina Guatteri, Gianmario Tessitore
https://arxiv.org/abs/2506.17094 htt…

Nonlinear random perturbations of Reaction-Diffusion Equations
This paper investigates the well-posedness and small-noise asymptotics of a class of stochastic partial differential equations defined on a bounded domain of $\mathbb{R}^d$, where the diffusion coefficient depends nonlinearly and non-locally on the solution through a conditional expectation. The reaction term is assumed to be merely continuous and to satisfy a quasi-dissipativity condition, without requiring any growth bounds or local Lipschitz continuity. This setting introduces significant an…

The Implementability of Liberalism
H\'ector Hermida-Rivera
https://arxiv.org/abs/2506.16059 https://arxiv.org/pdf/2506.16059

The Implementability of Liberalism
This note shows that under the unrestricted domain, there exists a choice liberal and Nash implementable social choice rule if and only if there are at least three players and the outcome set is at least twice as large as the player set. A social choice rule is choice liberal if and only if for every player, there exists at least one pair of outcomes such that if this player strictly prefers one over the other, the one he prefers is socially desirable and the other one is not. A social choice r…

I think that "chatbot" is a bad design paradigm for most problems. It's actually the refusal to to design work.
https://tante.cc/2025/06/19/chatbot-is-bad-design/

"ChatBot" is bad design
As anyone who has every seen anything I created knows: I am not a designer. So take my reasoning and thinking here with a grain of salt. I do have many designers amongst my friends and I do think that a lot of software engineering falls within the domain of design to a certain degree. […]

The Hexablock: a domain associated with the $\mu$-synthesis in $M_2(\mathbb C)$
Indranil Biswas, Sourav Pal, Nitin Tomar
https://arxiv.org/abs/2506.15149 h…

The Hexablock: a domain associated with the $μ$-synthesis in $M_2(\mathbb C)$
We study a new domain in $\mathbb C^4$, namely the hexablock $\mathbb{H}$ that arises in connection with a special case of the $μ$-synthesis problem in $M_2(\mathbb C)$. Previous attempts to study a few instances of the $μ$-synthesis problem led to domains such as symmetrized bidisc $\mathbb G_2$, tetrablock $\mathbb E$ and pentablock $\mathbb P$. Throughout, the relations of $\mathbb{H}$ with these three domains are explored. Several characterizations of the hexablock are established. We det…

BotTrans: A Multi-Source Graph Domain Adaptation Approach for Social Bot Detection
Boshen Shi, Yongqing Wang, Fangda Guo, Jiangli Shao, Huawei Shen, Xueqi Cheng
https://arxiv.org/abs/2506.13795

BotTrans: A Multi-Source Graph Domain Adaptation Approach for Social Bot Detection
Transferring extensive knowledge from relevant social networks has emerged as a promising solution to overcome label scarcity in detecting social bots and other anomalies with GNN-based models. However, effective transfer faces two critical challenges. Firstly, the network heterophily problem, which is caused by bots hiding malicious behaviors via indiscriminately interacting with human users, hinders the model's ability to learn sufficient and accurate bot-related knowledge from source domains…

This https://arxiv.org/abs/2505.02515 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

FedSDAF: Leveraging Source Domain Awareness for Enhanced Federated Domain Generalization
Traditional domain generalization approaches predominantly focus on leveraging target domain-aware features while overlooking the critical role of source domain-specific characteristics, particularly in federated settings with inherent data isolation. To address this gap, we propose the Federated Source Domain Awareness Framework (FedSDAF), the first method to systematically exploit source domain-aware features for enhanced federated domain generalization (FedDG). The FedSDAF framework consists…

Heterotopic energy for Sobolev mappings
Antoine Detaille, Jean Van Schaftingen
https://arxiv.org/abs/2506.16204 https://arxiv.org/pdf…

Heterotopic energy for Sobolev mappings
We study the notion of heterotopic energy defined as the limit of Sobolev energies of Sobolev mappings in a given homotopy class approximating almost everywhere a given Sobolev mapping. We show that the heterotopic energy is finite if and only if the mappings in the corresponding homotopy classes are homotopic on a codimension one skeleton of a triangulation of the domain. When this is the case, the heterotopic energy of a mapping is the sum of its Sobolev energy and its disparity energy, defin…

Heute vor 63 Jahren: Am 21.06.1962 zündeten die #USA im Rahmen von Operation Nougat die 36. Atombombe "Daman I". Nougat war eine Serie von #Kernwaffentests bei der 61/62 insgesamt 45 Bomben im Testgebiet in #Nevada

Electric field measurements made in space
Forrest Mozer, Oleksiy Agapitov
https://arxiv.org/abs/2505.14979 https://arxiv.org/pdf/2505…

Electric field measurements made in space
The operating principles of a DC and low frequency electric field detector are developed, after which, examples of earlier important electric field measurements are presented, including, the first observation of parallel electric fields in the auroral acceleration region, the first observation of time domain structures in space, the first experimental verification of symmetric magnetic field reconnection, the first observations of triggered ion acoustic waves, and oblique whistlers that directl…

Vacuum Instability and False Vacuum Decay Induced by Domain Walls in the N2HDM
Mohamed Younes Sassi, Gudrid Moortgat-Pick
https://arxiv.org/abs/2506.14880 …

Vacuum Instability and False Vacuum Decay Induced by Domain Walls in the N2HDM
The Next-to-Two-Higgs-Doublet model (N2HDM) has a rich vacuum structure where multiple electroweak (EW) breaking minima, as well as CP and electric-charge breaking minima, can coexist. These minima can be deeper than the electroweak vacuum $v_{ew} \approx 246\text{ GeV}$ of our universe, making our vacuum metastable. In such a case, one needs to calculate the tunneling rate from the EW vacuum to the deeper minimum. If the lifetime of the EW vacuum is longer than the universe's age, our vacuum i…

Experimental Verification of a Time-Domain Load Identification Method for Single-Phase Circuits
Francisco M. Arrabal-Campos, Francisco G. Montoya, Jorge Ventura, Santiago S\'anchez-Acevedo, Raymundo E. Torres-Olguin, Francisco de Le\'on
https://arxiv.org/abs/2506.12593

Experimental Verification of a Time-Domain Load Identification Method for Single-Phase Circuits
This paper presents experimental validation of a time-domain load parameter determination method for single-phase circuits. The verification is performed in a state-of-the-art smart grid laboratory equipped with power hardware and real-time emulators. The proposed method enables the identification of circuit parameters using only instantaneous voltage and current measurements at the point of common coupling. The experimental setup includes a range of test cases covering linear and non-sinusoida…

Earlier this month, #TomPatterson released a free (public domain) print-quality physical map of maritime Southeast Asia. It could actually almost double as a map of SEA except the northern part of Myanmar is cut off. 🗺️
https://

Holographic Baryons as Quantum Hall Droplets
Francesco Bigazzi, Aldo Lorenzo Cotrone, Andrea Olzi, Jean-Loup Raymond
https://arxiv.org/abs/2506.16205 https…

Holographic Baryons as Quantum Hall Droplets
We provide a first-principle construction of baryons as quantum Hall droplets in single-flavor holographic QCD. The baryons are described as charged D6-branes with a circular boundary on a flavor D8-brane in the Type IIA backgrounds dual to the confining and non-confining phases. The holographic description allows us to calculate precisely their properties, such as mass and size. We also consider other objects with baryonic charge, such as vortons, domain walls with holes, and "sandwich vortons…

Multi-domain anomaly detection in a 5G network
Thomas Hoger (LAAS-SARA), Philippe Owezarski (LAAS-SARA)
https://arxiv.org/abs/2506.12070 https://

Multi-domain anomaly detection in a 5G network
With the advent of 5G, mobile networks are becoming more dynamic and will therefore present a wider attack surface. To secure these new systems, we propose a multi-domain anomaly detection method that is distinguished by the study of traffic correlation on three dimensions: temporal by analyzing message sequences, semantic by abstracting the parameters these messages contain, and topological by linking them in the form of a graph. Unlike traditional approaches, which are limited to considering …

interactome_pdz: PDZ-domain interactome (2005)
A network of PDZ-domain-mediated protein–protein binding interactions, extracted from the PDZBase database. Nodes represent proteins and an edge represents a binding interaction between two proteins.
This network has 212 nodes and 244 edges.
Tags: Biological, Protein interactions, Unweighted

This https://arxiv.org/abs/2504.02966 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

On deformation of perfectoid purity in Gorenstein domains
If $(R,\mathfrak{m})$ is a complete local ring of mixed characteristic $(0,p)$ and $R/pR$ is an $F$-pure Gorenstein domain, we find a sufficient condition for $R$ to be perfectoid pure. This condition is related to the Cohen-Macaulayness of the absolute integral closures of Gorenstein local domains of mixed characteristic which are not necessarily excellent. Along the way, we show that the problem of lifting $F$-purity of $R/pR$ to perfectoid purity of $R$ is equivalent to a similar deformation…

Ah yes, I really dislike it when, as someone who is autistic, I don’t look before I accidentally block the entire Mastodon.social domain instead of just blocking a specific bot user.
Great, now over 100 lost me in their feeds. My day is ruined.
Domain unblocked, please boost for my visibility again!
#ActuallyAutistic

An efficient co-simulation and control approach to tackle complex multi-domain energetic systems: concepts and applications of the PEGASE platform
Mathieu Vallee (DTCH), Roland Baviere (DTCH), Val\'erie Seguin (DTCH), Val\'ery Vuillerme (DTCH), Nicolas Lamaison (DTCH), Michael Nikhil Descamps (DTCH), Antoine Aurousseau (DTCH)
https://

An efficient co-simulation and control approach to tackle complex multi-domain energetic systems: concepts and applications of the PEGASE platform
In this paper, we present a novel research software, called PEGASE, suitable for the design, validation and deployment of advanced control strategies for complex multi-domain energy systems. PEGASE especially features a highly efficient cosimulation engine, together with integrated solutions for defining both rule-based control strategies and Model-Predictive Control (MPC). The main principle behind the PEGASE platform is divide-and-conquer. Indeed, rather than trying to solve a problem as a mo…

Time-domain decoding of unconventional charge order mechanisms in nonmagnetic and magnetic kagome metals
Seongyong Lee, Byungjune Lee, Hoyoung Jang, Xueliang Wu, Jimin Kim, Gyeongbo Kang, Choongjae Won, Hyeongi Choi, Sang-Youn Park, Kyle M. Shen, Federico Cilento, Aifeng Wang, Jae-Hoon Park, Mingu Kang
https://arxiv.org/abs/2506…

Time-domain decoding of unconventional charge order mechanisms in nonmagnetic and magnetic kagome metals
In kagome lattice materials, quantum interplay between charge, spin, orbital, and lattice degrees of freedom gives rise to a remarkably rich set of emergent phenomena, ranging from unconventional charge order and superconductivity to topological magnetism. While the exact nature of these exotic orders is often challenging to comprehend in static experiments, time-resolved techniques can offer critical insights by disentangling coupled degrees of freedom on the time-axis. In this work, we demons…

Sacks-Uhlenbeck type regularity for subcritical generalized $p$-harmonic maps into Homogeneous targets
Gianmichele Di Matteo, Tobias Lamm
https://arxiv.org/abs/2506.17151

Sacks-Uhlenbeck type regularity for subcritical generalized $p$-harmonic maps into Homogeneous targets
Adapting \cite{strz3}, we define generalized $p$-harmonic maps into Riemannian homogeneous targets, a notion of solutions not belonging to the energy space. Restricting our attention to the subcritical range $p$ greater than the domain dimension $n$, we show a uniform $C^{1,α}$-regularity result for a sequence of such maps in the limit $p \searrow n$, assuming a uniform $n$-energy bound on its elements. The method of the proof follows the exact same lines as in \cite{strz3} but we need to chec…

So. Alle alten E-Mail-Aliase aufgeräumt und falls noch benötigt in -Adressen bei den relevanten Konten umgewandelt.
Bald kann dann wieder eine Domain zu @…
Und zwei weitere von Kunden sind noch auf dem Weg dahin.

GaussMarker: Robust Dual-Domain Watermark for Diffusion Models
Kecen Li, Zhicong Huang, Xinwen Hou, Cheng Hong
https://arxiv.org/abs/2506.11444 https://

GaussMarker: Robust Dual-Domain Watermark for Diffusion Models
As Diffusion Models (DM) generate increasingly realistic images, related issues such as copyright and misuse have become a growing concern. Watermarking is one of the promising solutions. Existing methods inject the watermark into the single-domain of initial Gaussian noise for generation, which suffers from unsatisfactory robustness. This paper presents the first dual-domain DM watermarking approach using a pipelined injector to consistently embed watermarks in both the spatial and frequency d…

Deaths by domain of protest over 12 Bolivian presidencies.
Same data, same graphing technique, but sorting the categories (by which occurs across the most bins) brings visual order to this data visualization. #dataviz #rstats

Enhancing Human-Robot Collaboration: A Sim2Real Domain Adaptation Algorithm for Point Cloud Segmentation in Industrial Environments
Fatemeh Mohammadi Amin, Darwin G. Caldwell, Hans Wernher van de Venn
https://arxiv.org/abs/2506.09552

Enhancing Human-Robot Collaboration: A Sim2Real Domain Adaptation Algorithm for Point Cloud Segmentation in Industrial Environments
The robust interpretation of 3D environments is crucial for human-robot collaboration (HRC) applications, where safety and operational efficiency are paramount. Semantic segmentation plays a key role in this context by enabling a precise and detailed understanding of the environment. Considering the intense data hunger for real-world industrial annotated data essential for effective semantic segmentation, this paper introduces a pioneering approach in the Sim2Real domain adaptation for semantic…

Large Language Models -- the Future of Fundamental Physics?
Caroline Heneka, Florian Nieser, Ayodele Ore, Tilman Plehn, Daniel Schiller
https://arxiv.org/abs/2506.14757

Large Language Models -- the Future of Fundamental Physics?
For many fundamental physics applications, transformers, as the state of the art in learning complex correlations, benefit from pretraining on quasi-out-of-domain data. The obvious question is whether we can exploit Large Language Models, requiring proper out-of-domain transfer learning. We show how the Qwen2.5 LLM can be used to analyze and generate SKA data, specifically 3D maps of the cosmological large-scale structure for a large part of the observable Universe. We combine the LLM with conn…

MoE-MLoRA for Multi-Domain CTR Prediction: Efficient Adaptation with Expert Specialization
Ken Yagel, Eyal German, Aviel Ben Siman Tov
https://arxiv.org/abs/2506.07563

MoE-MLoRA for Multi-Domain CTR Prediction: Efficient Adaptation with Expert Specialization
Personalized recommendation systems must adapt to user interactions across different domains. Traditional approaches like MLoRA apply a single adaptation per domain but lack flexibility in handling diverse user behaviors. To address this, we propose MoE-MLoRA, a mixture-of-experts framework where each expert is first trained independently to specialize in its domain before a gating network is trained to weight their contributions dynamically. We evaluate MoE-MLoRA across eight CTR models on Mov…

Arboreal representations of linear groups
Jorge Fari\~na-Asategui
https://arxiv.org/abs/2506.12745 https://arxiv.org/pdf/2506.12745…

Arboreal representations of linear groups
Abért and Virág conjectured in 2005 that any embedding of a linear group over a pro-$p$ domain into the group of $p$-adic automorphisms $W_p$ should be zero-dimensional. We prove their conjecture in greater generality, namely for embeddings of linear groups over any integral domain into the automorphism group of a bounded rooted tree.

More collages of public domain art
I started making some filler assets (grass etc) and found some cool carts as well. Haven't uploaded them yet but I will once I have enough

Datrics Text2SQL: A Framework for Natural Language to SQL Query Generation
Tetiana Gladkykh, Kyrylo Kirykov
https://arxiv.org/abs/2506.12234 https://

Datrics Text2SQL: A Framework for Natural Language to SQL Query Generation
Text-to-SQL systems enable users to query databases using natural language, democratizing access to data analytics. However, they face challenges in understanding ambiguous phrasing, domain-specific vocabulary, and complex schema relationships. This paper introduces Datrics Text2SQL, a Retrieval-Augmented Generation (RAG)-based framework designed to generate accurate SQL queries by leveraging structured documentation, example-based learning, and domain-specific rules. The system builds a rich K…

My friend as moved his main domain from .nl to .eu , Interesting move.
#Apple #iPhone

ALEA IACTA EST: A Declarative Domain-Specific Language for Manually Performable Random Experiments
Baltasar Tranc\'on y Widemann, Markus Lepper
https://arxiv.org/abs/2506.11794

ALEA IACTA EST: A Declarative Domain-Specific Language for Manually Performable Random Experiments
Random experiments that are simple and clear enough to be performed by human agents feature prominently in the teaching of elementary stochastics as well as in games. We present Alea, a domain-specific language for the specification of random experiments. Alea code can either be analyzed statically to obtain and inspect probability distributions of outcomes, or be executed with a source pseudo-randomness for simulation or as a game assistant. The language is intended for ease of use by non-expe…

Impact of a Deployed LLM Survey Creation Tool through the IS Success Model
Peng Jiang, Vinicius Cezar Monteiro de Lira, Antonio Maiorino
https://arxiv.org/abs/2506.14809

Impact of a Deployed LLM Survey Creation Tool through the IS Success Model
Surveys are a cornerstone of Information Systems (IS) research, yet creating high-quality surveys remains labor-intensive, requiring both domain expertise and methodological rigor. With the evolution of large language models (LLMs), new opportunities emerge to automate survey generation. This paper presents the real-world deployment of an LLM-powered system designed to accelerate data collection while maintaining survey quality. Deploying such systems in production introduces real-world complex…

Time-domain field correlation measurements enable tomography of highly multimode quantum states of light
Emanuel Hubenschmid, Guido Burkard
https://arxiv.org/abs/2506.10483

Time-domain field correlation measurements enable tomography of highly multimode quantum states of light
Recent progress in ultrafast optics facilitates the investigation of the dynamics of highly multimode quantum states of light, as demonstrated by the application of electro-optic sampling to quantum states of the electromagnetic field. Yet, the complete tomographic reconstruction of optical quantum states with prior unknown statistics and dynamics is still challenging, since state-of-the-art tomographic methods require the measurement of many orthogonal, distinguishable modes. Here, we propose …

Simultaneous Charge Carrier Density Mapping of SiC Epilayers and Substrates with Terahertz Time-Domain Spectroscopy
Joshua Hennig, Jens Klier, Stefan Duran, Kuei-Shen Hsu, Jan Beyer, Christian Roeder, Franziska C. Beyer, Nadine Schueler, Nico Vieweg, Katja Dutzi, Georg von Freymann, Daniel Molter
https://arxiv.org/abs/2506.14945…

Simultaneous Charge Carrier Density Mapping of SiC Epilayers and Substrates with Terahertz Time-Domain Spectroscopy
With the growing demand for efficient power electronics, SiC-based devices are progressively becoming more relevant. In contrast to established methods such as the mercury capacitance-voltage technique, terahertz spectroscopy promises a contactless characterization. In this work, we simultaneously determine the charge carrier density of SiC epilayers and their substrates in a single measurement over a wide range of about 8x10^(15)$ cm^(-3) to 4x10^(18) cm^(-3) using time-domain spectroscopy in …

Enhancing Taiji's Parameter Estimation under Non-Stationarity: a Time-Frequency Domain Framework for Galactic Binaries and Instrumental Noises
Minghui Du, Ziren Luo, Peng Xu
https://arxiv.org/abs/2506.10599

Enhancing Taiji's Parameter Estimation under Non-Stationarity: a Time-Frequency Domain Framework for Galactic Binaries and Instrumental Noises
The data analysis of space-based gravitational wave detectors like Taiji faces significant challenges from non-stationary noise, which compromises the efficacy of traditional frequency-domain analysis. This work proposes a unified framework based on short-time Fourier transform (STFT) to enhance parameter estimation of Galactic binary and characterization of instrumental noise under non-stationarity. Segmenting data into locally stationary intervals, we derive STFT-based models for signals and …

Collaborative Editable Model
Kaiwen Tang, Aitong Wu, Yao Lu, Guangda Sun
https://arxiv.org/abs/2506.14146 https://arxiv.org/pdf/2506.…

Collaborative Editable Model
Vertical-domain large language models (LLMs) play a crucial role in specialized scenarios such as finance, healthcare, and law; however, their training often relies on large-scale annotated data and substantial computational resources, impeding rapid development and continuous iteration. To address these challenges, we introduce the Collaborative Editable Model (CoEM), which constructs a candidate knowledge pool from user-contributed domain snippets, leverages interactive user-model dialogues c…

This https://arxiv.org/abs/2312.17294 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSE_…

Enhancing Open-Domain Task-Solving Capability of LLMs via Autonomous Tool Integration from GitHub
Large Language Models (LLMs) excel in traditional natural language processing tasks but struggle with problems that require complex domain-specific calculations or simulations. While equipping LLMs with external tools to build LLM-based agents can enhance their capabilities, existing approaches lack the flexibility to address diverse and ever-evolving user queries in open domains. Currently, there is also no existing dataset that evaluates LLMs on open-domain knowledge that requires tools to so…

H\"older continuity of Minimizing $W^{s,p}$-Harmonic Maps
Akshara Vincent
https://arxiv.org/abs/2506.16442 https://arxiv.org/pdf…

Hölder continuity of Minimizing $W^{s,p}$-Harmonic Maps
We show that the mappings $u\in \dot{W}^{s,p}(\mathbb{R}^n,\mathcal{N})$ into manifolds $\mathcal{N}$ of a sufficiently simple topology that minimize the energy $$\int_{\mathbb{R}^n}\int_{\mathbb{R}^n}\frac{|u(x)-u(y)|^p}{|x-y|^{n+sp}} \;dx\;dy$$ are locally Hölder continuous in a bounded domain $Ω$ outside a singular set $Σ$ with Hausdorff dimension strictly smaller than $n-sp$. We avoid the use of a monotonicity formula (which is unknown if $p \neq 2$) by using a blow-u…

Towards Reliable WMH Segmentation under Domain Shift: An Application Study using Maximum Entropy Regularization to Improve Uncertainty Estimation
Franco Matzkin, Agostina Larrazabal, Diego H Milone, Jose Dolz, Enzo Ferrante
https://arxiv.org/abs/2506.14497

Towards Reliable WMH Segmentation under Domain Shift: An Application Study using Maximum Entropy Regularization to Improve Uncertainty Estimation
Accurate segmentation of white matter hyperintensities (WMH) is crucial for clinical decision-making, particularly in the context of multiple sclerosis. However, domain shifts, such as variations in MRI machine types or acquisition parameters, pose significant challenges to model calibration and uncertainty estimation. This study investigates the impact of domain shift on WMH segmentation by proposing maximum-entropy regularization techniques to enhance model calibration and uncertainty estimat…

Making deep neural networks work for medical audio: representation, compression and domain adaptation
Charles C Onu
https://arxiv.org/abs/2506.13970 https:…

Making deep neural networks work for medical audio: representation, compression and domain adaptation
This thesis addresses the technical challenges of applying machine learning to understand and interpret medical audio signals. The sounds of our lungs, heart, and voice convey vital information about our health. Yet, in contemporary medicine, these sounds are primarily analyzed through auditory interpretation by experts using devices like stethoscopes. Automated analysis offers the potential to standardize the processing of medical sounds, enable screening in low-resource settings where physici…

Error Rates for Large Deviations in the domain of an $\alpha=1$ stable law
Jonny Imbierski, Dalia Terhesiu
https://arxiv.org/abs/2506.12443 https://…

Error Rates for Large Deviations in the domain of an $α=1$ stable law
We obtain error rates for large deviations of sums of i.i.d. random variables in, a particular case, of the domain of a non-symmetric infinite mean $α=1$-stable law. The focus of this work is on the method of proof via analytic techniques rather than the particular result.

At this year's Berlin Buzzwords, join Evgeniya Sukhodolskaya as she presents miniCOIL—a novel approach to creating a sparse neural retrieval model. This model aims to combine the advantages of dense and lexical retrieval methods while avoiding their drawbacks. Evgeniya will explain how to design and train a lightweight model that performs well on out-of-domain data and will demonstrate its capabilities.
Learn more:

Existence of weak solutions for two-phase matrix-valued harmonic map flows
Wei Wang, Wei Wang, Zhifei Zhang
https://arxiv.org/abs/2506.16278 https://

Existence of weak solutions for two-phase matrix-valued harmonic map flows
We investigate the existence of weak solutions for matrix-valued two-phase harmonic map flows with optimal lifespan, which arises as the limiting system of the matrix-valued Rubinstein-Sternberg-Keller problem studied by ({\em Invent. Math.}, 233(1):1--80, 2023). Our approach employs a modified minimizing movement scheme, discretizing the time domain and constructing approximate solutions by interpolating solutions to the associated functional problem within each small time interval.

Heute vor 41 Jahren: Am 20. Juni 1984 zündeten die USA im Rahmen von #Fusileer die #Atombombe "Duoro". Fusileer war eine Serie von Tests zwischen 83/84 bei der insgesamt 17 unterirdische #Kernwaffentests

Replaced article(s) found for cs.CV. https://arxiv.org/list/cs.CV/new
[3/4]:
- RoCA: Robust Cross-Domain End-to-End Autonomous Driving
Yasarla, Han, Cheng, Liu, Mahajan, Bhattacharyya, Shi, Garrepalli, Cai, Porikli

On finite factorization Puiseux algebras
Mohamed Benelmekki
https://arxiv.org/abs/2506.11793 https://arxiv.org/pdf/2506.11793

On finite factorization Puiseux algebras
An integral domain $D$ is called a finite factorization domain (FFD) if every nonzero nonunit element of $D$ has only finitely many non-associate divisors. In 1998, for an integral domain $D$ and a cancellative torsion-free monoid $S$ such that each nonzero element of its quotient group is of type $(0,0, \ldots)$, Kim proved that the monoid domain $D[S]$ is an FFD if and only if $D$ is an FFD and $S$ is an FFM. However, it is still open whether a monoid algebra $K[S]$ is an FFD provided that $S…

An optimal two-side Robin-Robin domain decomposition method for H(div)-elliptic problem
Na Xuyang
https://arxiv.org/abs/2506.12485 https://

An optimal two-side Robin-Robin domain decomposition method for H(div)-elliptic problem
In this paper, we develop a new two-side Robin-Robin domain decomposition method for H(div)-elliptic problem. Numerical results show that the convergence rate of the new algorithm only depends on $H/h$, where $H$ is diameter of subdomains and $h$ is the mesh size. Besides, an algebraic system of Robin boundary conditions is derived from the iterative method. We solve it by MINRES and get asymptotically stable iteration numbers as well.

Boundedness and asymptotic stability of classical solutions to a model for tuberculosis granuloma formation
Masaaki Mizukami, Yuya Tanaka
https://arxiv.org/abs/2506.16752

Boundedness and asymptotic stability of classical solutions to a model for tuberculosis granuloma formation
This paper deals with a problem which describes tuberculosis granuloma formation \begin{align*} \begin{cases} u_t = Δu - \nabla \cdot (u \nabla v) - uv - u + β, &x \in Ω,\ t>0, \\ v_t = Δv + v -uv + μw, &x \in Ω,\ t>0, \\ w_t = Δw + uv - wz - w, &x \in Ω,\ t>0, \\ z_t = Δz - \nabla \cdot (z \nabla w) + f(w)z -z, &x \in Ω,\ t>0 \end{cases} \end{align*} under homogeneous Neumann boundary conditions and initial conditions, where $Ω\subset \mathbb{R}^n$ ($n\ge 2$) is a smooth bounded …

Harvard releases Institutional Books 1.0, a dataset for AI researchers with 242B tokens, from 394M scanned pages and 983K public domain books in 254 languages (Matt O'Brien/Associated Press)
https://apnews.com/article/ai-chatbot-

crossMoDA Challenge: Evolution of Cross-Modality Domain Adaptation Techniques for Vestibular Schwannoma and Cochlea Segmentation from 2021 to 2023
Navodini Wijethilake, Reuben Dorent, Marina Ivory, Aaron Kujawa, Stefan Cornelissen, Patrick Langenhuizen, Mohamed Okasha, Anna Oviedova, Hexin Dong, Bogyeong Kang, Guillaume Sall\'e, Luyi Han, Ziyuan Zhao, Han Liu, Tao Yang, Shahad Hardan, Hussain Alasmawi, Santosh Sanjeev, Yuzhou Zhuang, Satoshi Kondo, Maria Baldeon Calisto, Shaikh Muh…

crossMoDA Challenge: Evolution of Cross-Modality Domain Adaptation Techniques for Vestibular Schwannoma and Cochlea Segmentation from 2021 to 2023
The cross-Modality Domain Adaptation (crossMoDA) challenge series, initiated in 2021 in conjunction with the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), focuses on unsupervised cross-modality segmentation, learning from contrast-enhanced T1 (ceT1) and transferring to T2 MRI. The task is an extreme example of domain shift chosen to serve as a meaningful and illustrative benchmark. From a clinical application perspective, it aims to automate Ve…

Chiral non-Abelian domain walls in dense QCD
Sven Bjarke Gudnason, Muneto Nitta
https://arxiv.org/abs/2506.08819 https://arxiv.org/pd…

Chiral non-Abelian domain walls in dense QCD
In this paper, we study chiral non-Abelian domain walls in a phase of unconventional vacua of dense QCD. The phase is characterized by asymmetric vacuum-expectation values (VEVs), for example with the left scalar field, corresponding to the left quark-quark condensate, having a nonvanishing VEV and the right field having a vanishing one. The domain wall soliton interpolates between this vacuum and another where the left and right scalar fields switch roles. We contemplate that such vacua could …

Video-Guided Text-to-Music Generation Using Public Domain Movie Collections
Haven Kim, Zachary Novack, Weihan Xu, Julian McAuley, Hao-Wen Dong
https://arxiv.org/abs/2506.12573

Video-Guided Text-to-Music Generation Using Public Domain Movie Collections
Despite recent advancements in music generation systems, their application in film production remains limited, as they struggle to capture the nuances of real-world filmmaking, where filmmakers consider multiple factors-such as visual content, dialogue, and emotional tone-when selecting or composing music for a scene. This limitation primarily stems from the absence of comprehensive datasets that integrate these elements. To address this gap, we introduce Open Screen Sound Library (OSSL), a dat…

Heute vor 63 Jahren: Am 20. Juni 1962 wurde ein Thor-Missile der US-Starfish-Testserie nach einer Minute Flug abgebrochen. Ohne nukleare Explosion fielen kontaminierte Teile auf Johnson Island, wo Personal lebte und arbeitete.

Understanding Lookahead Dynamics Through Laplace Transform
Aniket Sanyal, Tatjana Chavdarova
https://arxiv.org/abs/2506.13712 https://

Understanding Lookahead Dynamics Through Laplace Transform
We introduce a frequency-domain framework for convergence analysis of hyperparameters in game optimization, leveraging High-Resolution Differential Equations (HRDEs) and Laplace transforms. Focusing on the Lookahead algorithm--characterized by gradient steps $k$ and averaging coefficient $α$--we transform the discrete-time oscillatory dynamics of bilinear games into the frequency domain to derive precise convergence criteria. Our higher-precision $O(γ^2)$-HRDE models yield tighter criteria, w…

This https://arxiv.org/abs/2505.16764 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csPL_…

Can a domain-specific language improve program structure comprehension of data pipelines? A mixed-methods study
In many application domains, domain-specific languages can allow domain experts to contribute to collaborative projects more correctly and efficiently. To do so, they must be able to understand program structure from reading existing source code. With high-quality data becoming an increasingly important resource, the creation of data pipelines is an important application domain for domain-specific languages. We execute a mixed-method study consisting of a controlled experiment and a follow-up…

CWGAN-GP Augmented CAE for Jamming Detection in 5G-NR in Non-IID Datasets
Samhita Kuili, Mohammadreza Amini, Burak Kantarci
https://arxiv.org/abs/2506.15075

CWGAN-GP Augmented CAE for Jamming Detection in 5G-NR in Non-IID Datasets
In the ever-expanding domain of 5G-NR wireless cellular networks, over-the-air jamming attacks are prevalent as security attacks, compromising the quality of the received signal. We simulate a jamming environment by incorporating additive white Gaussian noise (AWGN) into the real-world In-phase and Quadrature (I/Q) OFDM datasets. A Convolutional Autoencoder (CAE) is exploited to implement a jamming detection over various characteristics such as heterogenous I/Q datasets; extracting relevant inf…

FormGym: Doing Paperwork with Agents
Matthew Toles, Rattandeep Singh, Isaac Song Zhou Yu
https://arxiv.org/abs/2506.14079 https://arx…

FormGym: Doing Paperwork with Agents
Completing paperwork is a challenging and time-consuming problem. Form filling is especially challenging in the pure-image domain without access to OCR, typeset PDF text, or a DOM. For computer agents, it requires multiple abilities, including multi-modal understanding, information retrieval, and tool-use. We present a novel form-filling benchmark consisting of 432 fields spread across 55 documents and 3 tasks, requiring knowledge of 236 features per user. We find that baseline VLAs achieve les…

Replaced article(s) found for cs.CV. https://arxiv.org/list/cs.CV/new
[1/3]:
Maximizing Information in Domain-Invariant Representation Improves Transfer Learning

Level-3 large deviations for the white-forced 2D Navier-Stokes system in a bounded domain
Meng Zhao
https://arxiv.org/abs/2506.14119 https://

Level-3 large deviations for the white-forced 2D Navier-Stokes system in a bounded domain
We study the large deviations principle (LDP) of Donsker-Varadhan type for the white-forced Navier-Stokes system in a bounded domain. Under the assumption that the noise is non-degenerate, we establish level-2 and level-3 LDPs with rate functions given by the Donsker-Varadhan formulas. The proof relies on an improved version of Kifer's criterion, a lift argument inspired from [DV83], an improved abstract result on the large-time asymptotics of generalized Markov semigroups, and a delicate appro…

FAD-Net: Frequency-Domain Attention-Guided Diffusion Network for Coronary Artery Segmentation using Invasive Coronary Angiography
Nan Mu, Ruiqi Song, Xiaoning Li, Zhihui Xu, Jingfeng Jiang, Chen Zhao
https://arxiv.org/abs/2506.11454

FAD-Net: Frequency-Domain Attention-Guided Diffusion Network for Coronary Artery Segmentation using Invasive Coronary Angiography
Background: Coronary artery disease (CAD) remains one of the leading causes of mortality worldwide. Precise segmentation of coronary arteries from invasive coronary angiography (ICA) is critical for effective clinical decision-making. Objective: This study aims to propose a novel deep learning model based on frequency-domain analysis to enhance the accuracy of coronary artery segmentation and stenosis detection in ICA, thereby offering robust support for the stenosis detection and treatment of …

MECHA: Multithreaded and Efficient Cryptographic Hardware Access
Pratama Derry, Laksmono Agus Mahardika Ari, Iqbal Muhammad, Howon Kim
https://arxiv.org/abs/2506.15034

MECHA: Multithreaded and Efficient Cryptographic Hardware Access
This paper presents a multithread and efficient cryptographic hardware access (MECHA) for efficient and fast cryptographic operations that eliminates the need for context switching. Utilizing a UNIX domain socket, MECHA manages multiple requests from multiple applications simultaneously, resulting in faster processing and improved efficiency. We comprise several key components, including the Server thread, Client thread, Transceiver thread, and a pair of Sender and Receiver queues. MECHA design…

Toward Knowledge-Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human-AI Synergy
Hugon Lee, Hyeonbin Moon, Junhyeong Lee, Seunghwa RYu
https://arxiv.org/abs/2506.00056

Toward Knowledge-Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human-AI Synergy
Artificial intelligence (AI) is reshaping inverse design across manufacturing domain, enabling high-performance discovery in materials, products, and processes. However, purely data-driven approaches often struggle in realistic settings characterized by sparse data, high-dimensional design spaces, and nontrivial physical constraints. This perspective argues for a new generation of design systems that transcend black-box modeling by integrating domain knowledge, physics-informed learning, and in…

Breaking the Multi-Enhancement Bottleneck: Domain-Consistent Quality Enhancement for Compressed Images
Qunliang Xing, Mai Xu, Jing Yang, Shengxi Li
https://arxiv.org/abs/2506.14152

Breaking the Multi-Enhancement Bottleneck: Domain-Consistent Quality Enhancement for Compressed Images
Quality enhancement methods have been widely integrated into visual communication pipelines to mitigate artifacts in compressed images. Ideally, these quality enhancement methods should perform robustly when applied to images that have already undergone prior enhancement during transmission. We refer to this scenario as multi-enhancement, which generalizes the well-known multi-generation scenario of image compression. Unfortunately, current quality enhancement methods suffer from severe degrada…

EVA-S2PMLP: Secure and Scalable Two-Party MLP via Spatial Transformation
Shizhao Peng, Shoumo Li, Tianle Tao
https://arxiv.org/abs/2506.15102 https://

EVA-S2PMLP: Secure and Scalable Two-Party MLP via Spatial Transformation
Privacy-preserving neural network training in vertically partitioned scenarios is vital for secure collaborative modeling across institutions. This paper presents \textbf{EVA-S2PMLP}, an Efficient, Verifiable, and Accurate Secure Two-Party Multi-Layer Perceptron framework that introduces spatial-scale optimization for enhanced privacy and performance. To enable reliable computation under real-number domain, EVA-S2PMLP proposes a secure transformation pipeline that maps scalar inputs to vector a…

Integrating Knowledge Graphs and Bayesian Networks: A Hybrid Approach for Explainable Disease Risk Prediction
Mbithe Nzomo, Deshendran Moodley
https://arxiv.org/abs/2506.13920

Integrating Knowledge Graphs and Bayesian Networks: A Hybrid Approach for Explainable Disease Risk Prediction
Multimodal electronic health record (EHR) data is useful for disease risk prediction based on medical domain knowledge. However, general medical knowledge must be adapted to specific healthcare settings and patient populations to achieve practical clinical use. Additionally, risk prediction systems must handle uncertainty from incomplete data and non-deterministic health outcomes while remaining explainable. These challenges can be alleviated by the integration of knowledge graphs (KGs) and Bay…

ConStyX: Content Style Augmentation for Generalizable Medical Image Segmentation
Xi Chen, Zhiqiang Shen, Peng Cao, Jinzhu Yang, Osmar R. Zaiane
https://arxiv.org/abs/2506.10675

ConStyX: Content Style Augmentation for Generalizable Medical Image Segmentation
Medical images are usually collected from multiple domains, leading to domain shifts that impair the performance of medical image segmentation models. Domain Generalization (DG) aims to address this issue by training a robust model with strong generalizability. Recently, numerous domain randomization-based DG methods have been proposed. However, these methods suffer from the following limitations: 1) constrained efficiency of domain randomization due to their exclusive dependence on image style…

Med-REFL: Medical Reasoning Enhancement via Self-Corrected Fine-grained Reflection
Zongxian Yang, Jiayu Qian, Zegao Peng, Haoyu Zhang, Zhi-An Huang
https://arxiv.org/abs/2506.13793

Med-REFL: Medical Reasoning Enhancement via Self-Corrected Fine-grained Reflection
Large reasoning models have recently made significant strides in mathematical and code reasoning, yet their success has not transferred smoothly to the medical domain. While multiple factors contribute to this disparity, a critical issue is the inadequate focus on the quality of intermediate reflection steps, which is particularly crucial in high-stakes medical scenarios. To address this challenge, we propose Med-REFL, a \underline{\textbf{Med}}ical \underline{\textbf{R}}easoning \underline{\te…

Exploring the Effectiveness of Deep Features from Domain-Specific Foundation Models in Retinal Image Synthesis
Zuzanna Skorniewska, Bartlomiej W. Papiez
https://arxiv.org/abs/2506.11753

Exploring the Effectiveness of Deep Features from Domain-Specific Foundation Models in Retinal Image Synthesis
The adoption of neural network models in medical imaging has been constrained by strict privacy regulations, limited data availability, high acquisition costs, and demographic biases. Deep generative models offer a promising solution by generating synthetic data that bypasses privacy concerns and addresses fairness by producing samples for under-represented groups. However, unlike natural images, medical imaging requires validation not only for fidelity (e.g., Fréchet Inception Score) but also…

Improving Prostate Gland Segmenting Using Transformer based Architectures
Shatha Abudalou
https://arxiv.org/abs/2506.14844 https://ar…

Improving Prostate Gland Segmenting Using Transformer based Architectures
Inter reader variability and cross site domain shift challenge the automatic segmentation of prostate anatomy using T2 weighted MRI images. This study investigates whether transformer models can retain precision amid such heterogeneity. We compare the performance of UNETR and SwinUNETR in prostate gland segmentation against our previous 3D UNet model [1], based on 546 MRI (T2weighted) volumes annotated by two independent experts. Three training strategies were analyzed: single cohort dataset, 5…